Artificial intelligence (AI) systems can integrate data accumulation, recognition and storage functions with higher order analysis and decision protocols. AI systems such as expert systems and neural networks find wide application in qualitative analysis. Expert systems typically generate an individual data structure which is analyzed according to a knowledge base working in conjunction with a resident database; see, e.g. Holloway et al. (1993) U.S. Pat. No. 5,253,164 which was subject to recent judicial review, GMIS Inc, 34 USPQ2d 1389 (1995). "MYCIN", another example, is a computer protocol using individual clinical evaluations to generate a personal data structure which is analyzed according to a knowledge base to predict or diagnose myocardial infarction and to determine hospital admissibility (Goldman et al. (1988) New England Journal of Medicine 318,797-803).
Neural network systems are networks of interconnected processing elements, each of which can have multiple input signals, but generates only one output signal. A neural network is trained by inputting training set of signals and correlating responses. The trained network is then used to analyze novel signals. For example, neural networks have been used extensively in optical character and speech recognition applications (e.g. Colley et al. (1993) U.S. Pat. No. 5,251,268).
The analysis of complex systems such as biological organisms are particularly well-suited to AI systems. Otherwise intractable complex stimulus-response patterns can be effectively analyzed using deduction protocols applied through AI systems. Pharmaceutical development for example, requires large-scale studies of systemic responses to modifications of the structure, form or administration of a drug. Presently, such systemic information is usually provided by live animal models which are costly and provide limited, relatively uninformative output signals (death, weight loss, etc.) and often mask the myriad biochemical pathway repressions and activations which underlie the measured organismal response. A number of in vitro or cell culture-based methods have been described for identifying compounds with a particular biological effect through the activation of a linked reporter (e.g. Gadski et al. (1992) EP 92304902.7 describes methods for substances which regulate the synthesis of an apolipoprotein; Evans et al. (1991) U.S. Pat. No. 4,981,784 describes methods for identifying ligand for a receptor and Farr et al. (1994) WO 94/17208 describes methods and kits utilizing stress promoters to determine toxicity of a compound).
The present invention combines these approaches to provide an in vitro or cell culture-based analysis of systemic response patterns. In particular, the invention involves sophisticated methods for generating and analyzing highly informative stimulus--systemic repression and activation response patterns.